Papers - Pandas Profiling Report

Dataset statistics

Number of variables	16
Number of observations	287544
Missing cells	609
Missing cells (%)	< 0.1%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	17.7 MiB
Average record size in memory	64.4 B

Variable types

Numeric	9
Categorical	7

Warnings

`SC` has a high cardinality: 2649 distinct values	High cardinality
`Country` has a high cardinality: 177 distinct values	High cardinality
`CountryCode` has a high cardinality: 177 distinct values	High cardinality
`ArtsHumanities` is highly skewed (γ1 = 42.92297734)	Skewed
`TCperYear` is highly skewed (γ1 = 89.73195513)	Skewed
`NumAuthors` is highly skewed (γ1 = 21.17953762)	Skewed
`ArtsHumanities` has 287305 (99.9%) zeros	Zeros
`LifeSciencesBiomedicine` has 242657 (84.4%) zeros	Zeros
`PhysicalSciences` has 223642 (77.8%) zeros	Zeros
`SocialSciences` has 279391 (97.2%) zeros	Zeros
`Technology` has 54360 (18.9%) zeros	Zeros
`TCperYear` has 80888 (28.1%) zeros	Zeros

Reproduction

Analysis started	2021-01-14 14:46:17.824718
Analysis finished	2021-01-14 14:46:50.315475
Duration	32.49 seconds
Software version	pandas-profiling v2.10.0
Download configuration	config.yaml

PY
Real number (ℝ_≥0)

Distinct	29
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	2010.665651
Minimum	1990
Maximum	2018
Zeros	0
Zeros (%)	0.0%
Memory size	561.7 KiB

Quantile statistics

Minimum	1990
5-th percentile	1999
Q1	2006
median	2012
Q3	2016
95-th percentile	2018
Maximum	2018
Range	28
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	6.245364613
Coefficient of variation (CV)	0.003106117922
Kurtosis	-0.3513597005
Mean	2010.665651
Median Absolute Deviation (MAD)	5
Skewness	-0.7236493956
Sum	578154844
Variance	39.00457915
Monotocity	Not monotonic

Histogram with fixed size bins (bins=29)

Value	Count	Frequency (%)
2018	34202	11.9%
2017	28870	10.0%
2016	22408	7.8%
2015	20173	7.0%
2014	17061	5.9%
2013	15069	5.2%
2012	14000	4.9%
2009	14000	4.9%
2008	12879	4.5%
2011	12229	4.3%
Other values (19)	96653	33.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1990	72	< 0.1%
1991	391	0.1%
1992	674	0.2%
1993	834	0.3%
1994	994	0.3%

Value	Count	Frequency (%)
2018	34202	11.9%
2017	28870	10.0%
2016	22408	7.8%
2015	20173	7.0%
2014	17061	5.9%

SC
Categorical

HIGH CARDINALITY

Distinct	2649
Distinct (%)	0.9%
Missing	0
Missing (%)	0.0%
Memory size	662.4 KiB

Computer Science	44679
Computer Science; Engineering	26207
Engineering	21091
Automation & Control Systems; Engineering	5863
Physics	5589
Other values (2644)	184115

Length

Max length	188
Median length	29
Mean length	33.72064449
Min length	3

Characters and Unicode

Total characters	9696169
Distinct characters	49
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	592 ?
Unique (%)	0.2%

Sample

1st row	Computer Science; Engineering
2nd row	Computer Science; Engineering
3rd row	Computer Science; Engineering
4th row	Computer Science; Engineering
5th row	Computer Science; Engineering

Value	Count	Frequency (%)
Computer Science	44679	15.5%
Computer Science; Engineering	26207	9.1%
Engineering	21091	7.3%
Automation & Control Systems; Engineering	5863	2.0%
Physics	5589	1.9%
Computer Science; Neurosciences & Neurology	4587	1.6%
Science & Technology - Other Topics	4478	1.6%
Computer Science; Engineering; Telecommunications	4101	1.4%
Automation & Control Systems; Computer Science	4022	1.4%
Mathematics	3900	1.4%
Other values (2639)	163027	56.7%

Histogram of lengths of the category

Value	Count	Frequency (%)
science	170102	15.3%
	150429	13.5%
computer	123626	11.1%
engineering	121970	11.0%
technology	28080	2.5%
control	26581	2.4%
systems	26581	2.4%
automation	26581	2.4%
sciences	15715	1.4%
physics	15400	1.4%
Other values (201)	407409	36.6%

Most occurring characters

Value	Count	Frequency (%)
e	1146181	11.8%
n	874397	9.0%
	824930	8.5%
i	768671	7.9%
c	650290	6.7%
o	618226	6.4%
t	508312	5.2%
r	492410	5.1%
g	408748	4.2%
s	356006	3.7%
Other values (39)	3047998	31.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	7515874	77.5%
Uppercase Letter	962074	9.9%
Space Separator	824930	8.5%
Other Punctuation	381472	3.9%
Dash Punctuation	11819	0.1%

Most frequent character per category

Value	Count	Frequency (%)
e	1146181	15.3%
n	874397	11.6%
i	768671	10.2%
c	650290	8.7%
o	618226	8.2%
t	508312	6.8%
r	492410	6.6%
g	408748	5.4%
s	356006	4.7%
m	334039	4.4%
Other values (13)	1358594	18.1%

Value	Count	Frequency (%)
S	224139	23.3%
C	171583	17.8%
E	160617	16.7%
M	70224	7.3%
T	59958	6.2%
A	45338	4.7%
P	39954	4.2%
I	39125	4.1%
R	35080	3.6%
O	30068	3.1%
Other values (11)	85988	8.9%

Value	Count	Frequency (%)
;	239051	62.7%
&	138703	36.4%
,	3718	1.0%

Value	Count	Frequency (%)
	824930	100.0%

Value	Count	Frequency (%)
-	11819	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	8477948	87.4%
Common	1218221	12.6%

Most frequent character per script

Value	Count	Frequency (%)
e	1146181	13.5%
n	874397	10.3%
i	768671	9.1%
c	650290	7.7%
o	618226	7.3%
t	508312	6.0%
r	492410	5.8%
g	408748	4.8%
s	356006	4.2%
m	334039	3.9%
Other values (34)	2320668	27.4%

Value	Count	Frequency (%)
	824930	67.7%
;	239051	19.6%
&	138703	11.4%
-	11819	1.0%
,	3718	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	9696169	100.0%

Most frequent character per block

Value	Count	Frequency (%)
e	1146181	11.8%
n	874397	9.0%
	824930	8.5%
i	768671	7.9%
c	650290	6.7%
o	618226	6.4%
t	508312	5.2%
r	492410	5.1%
g	408748	4.2%
s	356006	3.7%
Other values (39)	3047998	31.4%

ArtsHumanities
Real number (ℝ_≥0)

SKEWED
ZEROS

Distinct	8
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	0.0005379135351
Minimum	0
Maximum	1
Zeros	287305
Zeros (%)	99.9%
Memory size	2.2 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	1
Range	1
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.02062099833
Coefficient of variation (CV)	38.33515424
Kurtosis	1954.44341
Mean	0.0005379135351
Median Absolute Deviation (MAD)	0
Skewness	42.92297734
Sum	154.6738095
Variance	0.0004252255723
Monotocity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
0	287305	99.9%
1	96	< 0.1%
0.5	91	< 0.1%
0.3333333333	20	< 0.1%
0.25	13	< 0.1%
0.2	7	< 0.1%
0.1666666667	6	< 0.1%
0.1428571429	6	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	287305	99.9%
0.1428571429	6	< 0.1%
0.1666666667	6	< 0.1%
0.2	7	< 0.1%
0.25	13	< 0.1%

Value	Count	Frequency (%)
1	96	< 0.1%
0.5	91	< 0.1%
0.3333333333	20	< 0.1%
0.25	13	< 0.1%
0.2	7	< 0.1%

LifeSciencesBiomedicine
Real number (ℝ_≥0)

ZEROS

Distinct	15
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	0.1095826521
Minimum	0
Maximum	1
Zeros	242657
Zeros (%)	84.4%
Memory size	2.2 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	1
Maximum	1
Range	1
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.2785685298
Coefficient of variation (CV)	2.542086036
Kurtosis	4.756714659
Mean	0.1095826521
Median Absolute Deviation (MAD)	0
Skewness	2.479240321
Sum	31509.83413
Variance	0.07760042582
Monotocity	Not monotonic

Histogram with fixed size bins (bins=15)

Value	Count	Frequency (%)
0	242657	84.4%
1	20320	7.1%
0.5	12311	4.3%
0.3333333333	7348	2.6%
0.6666666667	2388	0.8%
0.25	1303	0.5%
0.6	698	0.2%
0.75	126	< 0.1%
0.2	112	< 0.1%
0.1666666667	83	< 0.1%
Other values (5)	198	0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	242657	84.4%
0.1111111111	2	< 0.1%
0.1666666667	83	< 0.1%
0.2	112	< 0.1%
0.25	1303	0.5%

Value	Count	Frequency (%)
1	20320	7.1%
0.8333333333	74	< 0.1%
0.8	23	< 0.1%
0.75	126	< 0.1%
0.6666666667	2388	0.8%

PhysicalSciences
Real number (ℝ_≥0)

ZEROS

Distinct	16
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	0.1482194167
Minimum	0
Maximum	1
Zeros	223642
Zeros (%)	77.8%
Memory size	2.2 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	1
Maximum	1
Range	1
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.30871378
Coefficient of variation (CV)	2.082816049
Kurtosis	2.41000895
Mean	0.1482194167
Median Absolute Deviation (MAD)	0
Skewness	1.956151124
Sum	42619.60397
Variance	0.09530419794
Monotocity	Not monotonic

Histogram with fixed size bins (bins=16)

Value	Count	Frequency (%)
0	223642	77.8%
1	25316	8.8%
0.5	17618	6.1%
0.3333333333	10486	3.6%
0.6666666667	5237	1.8%
0.25	3237	1.1%
0.2	867	0.3%
0.4	792	0.3%
0.75	178	0.1%
0.6	68	< 0.1%
Other values (6)	103	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	223642	77.8%
0.1428571429	36	< 0.1%
0.1666666667	36	< 0.1%
0.2	867	0.3%
0.2222222222	2	< 0.1%

Value	Count	Frequency (%)
1	25316	8.8%
0.8	27	< 0.1%
0.75	178	0.1%
0.6666666667	5237	1.8%
0.6	68	< 0.1%

SocialSciences
Real number (ℝ_≥0)

ZEROS

Distinct	14
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	0.01971971495
Minimum	0
Maximum	1
Zeros	279391
Zeros (%)	97.2%
Memory size	2.2 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	1
Range	1
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.1256870244
Coefficient of variation (CV)	6.373673489
Kurtosis	48.1070608
Mean	0.01971971495
Median Absolute Deviation (MAD)	0
Skewness	6.88661225
Sum	5670.285714
Variance	0.01579722809
Monotocity	Not monotonic

Histogram with fixed size bins (bins=14)

Value	Count	Frequency (%)
0	279391	97.2%
1	3751	1.3%
0.5	2263	0.8%
0.3333333333	1047	0.4%
0.25	623	0.2%
0.6666666667	335	0.1%
0.2	38	< 0.1%
0.75	29	< 0.1%
0.6	28	< 0.1%
0.4	22	< 0.1%
Other values (4)	17	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	279391	97.2%
0.1428571429	1	< 0.1%
0.1666666667	10	< 0.1%
0.2	38	< 0.1%
0.25	623	0.2%

Value	Count	Frequency (%)
1	3751	1.3%
0.8	1	< 0.1%
0.75	29	< 0.1%
0.6666666667	335	0.1%
0.6	28	< 0.1%

Technology
Real number (ℝ_≥0)

ZEROS

Distinct	18
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	0.7219403026
Minimum	0
Maximum	1
Zeros	54360
Zeros (%)	18.9%
Memory size	2.2 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0.5
median	1
Q3	1
95-th percentile	1
Maximum	1
Range	1
Interquartile range (IQR)	0.5

Descriptive statistics

Standard deviation	0.3965653732
Coefficient of variation (CV)	0.5493049381
Kurtosis	-0.7235442184
Mean	0.7219403026
Median Absolute Deviation (MAD)	0
Skewness	-0.9796862641
Sum	207589.6024
Variance	0.1572640953
Monotocity	Not monotonic

Histogram with fixed size bins (bins=18)

Value	Count	Frequency (%)
1	179457	62.4%
0	54360	18.9%
0.5	27308	9.5%
0.6666666667	12278	4.3%
0.3333333333	7971	2.8%
0.75	3390	1.2%
0.6	780	0.3%
0.25	765	0.3%
0.2	729	0.3%
0.8	180	0.1%
Other values (8)	326	0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	54360	18.9%
0.1428571429	1	< 0.1%
0.1666666667	74	< 0.1%
0.2	729	0.3%
0.25	765	0.3%

Value	Count	Frequency (%)
1	179457	62.4%
0.8571428571	36	< 0.1%
0.8333333333	21	< 0.1%
0.8	180	0.1%
0.75	3390	1.2%

ComputerScience
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.2 MiB

0	163918
1	123626

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	287544
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Value	Count	Frequency (%)
0	163918	57.0%
1	123626	43.0%

Histogram of lengths of the category

Value	Count	Frequency (%)
0	163918	57.0%
1	123626	43.0%

Most occurring characters

Value	Count	Frequency (%)
0	163918	57.0%
1	123626	43.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	287544	100.0%

Most frequent character per category

Value	Count	Frequency (%)
0	163918	57.0%
1	123626	43.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	287544	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	163918	57.0%
1	123626	43.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	287544	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	163918	57.0%
1	123626	43.0%

Health
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	2.2 MiB

0	256531
1	31013

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	287544
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Value	Count	Frequency (%)
0	256531	89.2%
1	31013	10.8%

Histogram of lengths of the category

Value	Count	Frequency (%)
0	256531	89.2%
1	31013	10.8%

Most occurring characters

Value	Count	Frequency (%)
0	256531	89.2%
1	31013	10.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	287544	100.0%

Most frequent character per category

Value	Count	Frequency (%)
0	256531	89.2%
1	31013	10.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	287544	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	256531	89.2%
1	31013	10.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	287544	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	256531	89.2%
1	31013	10.8%

NR
Real number (ℝ_≥0)

Distinct	402
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	30.23000306
Minimum	1
Maximum	1972
Zeros	0
Zeros (%)	0.0%
Memory size	561.7 KiB

Quantile statistics

Minimum	1
5-th percentile	6
Q1	14
median	24
Q3	38
95-th percentile	72
Maximum	1972
Range	1971
Interquartile range (IQR)	24

Descriptive statistics

Standard deviation	27.74537999
Coefficient of variation (CV)	0.9178093676
Kurtosis	234.6164263
Mean	30.23000306
Median Absolute Deviation (MAD)	11
Skewness	7.514348762
Sum	8692456
Variance	769.8061108
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
12	8370	2.9%
15	8352	2.9%
10	8189	2.8%
16	7976	2.8%
11	7953	2.8%
14	7951	2.8%
13	7782	2.7%
18	7504	2.6%
17	7494	2.6%
20	7478	2.6%
Other values (392)	208495	72.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	251	0.1%
2	663	0.2%
3	1496	0.5%
4	2643	0.9%
5	4155	1.4%

Value	Count	Frequency (%)
1972	2	< 0.1%
1073	1	< 0.1%
882	1	< 0.1%
863	3	< 0.1%
770	1	< 0.1%

TCperYear
Real number (ℝ_≥0)

SKEWED
ZEROS

Distinct	3692
Distinct (%)	1.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	1.762959954
Minimum	0
Maximum	1587.8
Zeros	80888
Zeros (%)	28.1%
Memory size	2.2 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0.5
Q3	1.666666667
95-th percentile	7
Maximum	1587.8
Range	1587.8
Interquartile range (IQR)	1.666666667

Descriptive statistics

Standard deviation	7.645493537
Coefficient of variation (CV)	4.336736928
Kurtosis	15083.66167
Mean	1.762959954
Median Absolute Deviation (MAD)	0.5
Skewness	89.73195513
Sum	506928.5571
Variance	58.45357142
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	80888	28.1%
0.5	10892	3.8%
1	10531	3.7%
0.3333333333	7514	2.6%
0.25	5183	1.8%
2	4911	1.7%
0.6666666667	4726	1.6%
1.5	4027	1.4%
0.2	3768	1.3%
0.1666666667	2973	1.0%
Other values (3682)	152131	52.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	80888	28.1%
0.03333333333	6	< 0.1%
0.03448275862	27	< 0.1%
0.03571428571	31	< 0.1%
0.03703703704	50	< 0.1%

Value	Count	Frequency (%)
1587.8	2	< 0.1%
932.6	1	< 0.1%
853.5	1	< 0.1%
746	1	< 0.1%
558.6	1	< 0.1%

NumAuthors
Real number (ℝ_≥0)

SKEWED

Distinct	134
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	10.59242759
Minimum	0
Maximum	3049
Zeros	1
Zeros (%)	< 0.1%
Memory size	561.7 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	2
median	3
Q3	4
95-th percentile	7
Maximum	3049
Range	3049
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	124.5018182
Coefficient of variation (CV)	11.75385124
Kurtosis	467.5766407
Mean	10.59242759
Median Absolute Deviation (MAD)	1
Skewness	21.17953762
Sum	3045789
Variance	15500.70275
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
3	76402	26.6%
2	66743	23.2%
4	56909	19.8%
5	32157	11.2%
1	18916	6.6%
6	16108	5.6%
7	7745	2.7%
8	4018	1.4%
9	2226	0.8%
10	1352	0.5%
Other values (124)	4968	1.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	< 0.1%
1	18916	6.6%
2	66743	23.2%
3	76402	26.6%
4	56909	19.8%

Value	Count	Frequency (%)
3049	39	< 0.1%
3041	39	< 0.1%
2908	41	< 0.1%
2900	42	< 0.1%
2888	41	< 0.1%

Organisation
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	281.0 KiB

Collaboration	146062
Academia	130102
Company	11380

Length

Max length	13
Median length	13
Mean length	10.50024344
Min length	7

Characters and Unicode

Total characters	3019282
Distinct characters	16
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Collaboration
2nd row	Collaboration
3rd row	Collaboration
4th row	Collaboration
5th row	Academia

Value	Count	Frequency (%)
Collaboration	146062	50.8%
Academia	130102	45.2%
Company	11380	4.0%

Histogram of lengths of the category

Value	Count	Frequency (%)
collaboration	146062	50.8%
academia	130102	45.2%
company	11380	4.0%

Most occurring characters

Value	Count	Frequency (%)
a	563708	18.7%
o	449566	14.9%
l	292124	9.7%
i	276164	9.1%
C	157442	5.2%
n	157442	5.2%
b	146062	4.8%
r	146062	4.8%
t	146062	4.8%
m	141482	4.7%
Other values (6)	543168	18.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	2731738	90.5%
Uppercase Letter	287544	9.5%

Most frequent character per category

Value	Count	Frequency (%)
a	563708	20.6%
o	449566	16.5%
l	292124	10.7%
i	276164	10.1%
n	157442	5.8%
b	146062	5.3%
r	146062	5.3%
t	146062	5.3%
m	141482	5.2%
c	130102	4.8%
Other values (4)	282964	10.4%

Value	Count	Frequency (%)
C	157442	54.8%
A	130102	45.2%

Most occurring scripts

Value	Count	Frequency (%)
Latin	3019282	100.0%

Most frequent character per script

Value	Count	Frequency (%)
a	563708	18.7%
o	449566	14.9%
l	292124	9.7%
i	276164	9.1%
C	157442	5.2%
n	157442	5.2%
b	146062	4.8%
r	146062	4.8%
t	146062	4.8%
m	141482	4.7%
Other values (6)	543168	18.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3019282	100.0%

Most frequent character per block

Value	Count	Frequency (%)
a	563708	18.7%
o	449566	14.9%
l	292124	9.7%
i	276164	9.1%
C	157442	5.2%
n	157442	5.2%
b	146062	4.8%
r	146062	4.8%
t	146062	4.8%
m	141482	4.7%
Other values (6)	543168	18.0%

Region
Categorical

Distinct	9
Distinct (%)	< 0.1%
Missing	605
Missing (%)	0.2%
Memory size	281.3 KiB

NorthEast Asia	87043
Western Europe	63918
North America	47520
Eastern Europe to Central Asia	21930
MiddleEast and North Africa	19787
Other values (4)	46741

Length

Max length	30
Median length	14
Mean length	17.00028926
Min length	10

Characters and Unicode

Total characters	4878046
Distinct characters	27
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	North America
2nd row	SouthEast Asia and Pacific
3rd row	Western Europe
4th row	Western Europe
5th row	North America

Value	Count	Frequency (%)
NorthEast Asia	87043	30.3%
Western Europe	63918	22.2%
North America	47520	16.5%
Eastern Europe to Central Asia	21930	7.6%
MiddleEast and North Africa	19787	6.9%
SouthEast Asia and Pacific	18654	6.5%
South Asia	15998	5.6%
Latin America and Caribbean	10233	3.6%
Sub Saharan Africa	1856	0.6%
(Missing)	605	0.2%

Histogram of lengths of the category

Value	Count	Frequency (%)
asia	143625	19.4%
northeast	87043	11.8%
europe	85848	11.6%
north	67307	9.1%
western	63918	8.7%
america	57753	7.8%
and	48674	6.6%
to	21930	3.0%
eastern	21930	3.0%
central	21930	3.0%
Other values (9)	118914	16.1%

Most occurring characters

Value	Count	Frequency (%)
a	495960	10.2%
t	454427	9.3%
	451933	9.3%
r	439461	9.0%
s	354957	7.3%
e	345317	7.1%
i	300582	6.2%
o	296780	6.1%
E	233262	4.8%
A	223021	4.6%
Other values (17)	1282346	26.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	3632361	74.5%
Uppercase Letter	793752	16.3%
Space Separator	451933	9.3%

Most frequent character per category

Value	Count	Frequency (%)
a	495960	13.7%
t	454427	12.5%
r	439461	12.1%
s	354957	9.8%
e	345317	9.5%
i	300582	8.3%
o	296780	8.2%
h	190858	5.3%
n	178774	4.9%
u	122356	3.4%
Other values (7)	452889	12.5%

Value	Count	Frequency (%)
E	233262	29.4%
A	223021	28.1%
N	154350	19.4%
W	63918	8.1%
S	38364	4.8%
C	32163	4.1%
M	19787	2.5%
P	18654	2.4%
L	10233	1.3%

Value	Count	Frequency (%)
	451933	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4426113	90.7%
Common	451933	9.3%

Most frequent character per script

Value	Count	Frequency (%)
a	495960	11.2%
t	454427	10.3%
r	439461	9.9%
s	354957	8.0%
e	345317	7.8%
i	300582	6.8%
o	296780	6.7%
E	233262	5.3%
A	223021	5.0%
h	190858	4.3%
Other values (16)	1091488	24.7%

Value	Count	Frequency (%)
	451933	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4878046	100.0%

Most frequent character per block

Value	Count	Frequency (%)
a	495960	10.2%
t	454427	9.3%
	451933	9.3%
r	439461	9.0%
s	354957	7.3%
e	345317	7.1%
i	300582	6.2%
o	296780	6.1%
E	233262	4.8%
A	223021	4.6%
Other values (17)	1282346	26.3%

Country
Categorical

HIGH CARDINALITY

Distinct	177
Distinct (%)	0.1%
Missing	2
Missing (%)	< 0.1%
Memory size	568.1 KiB

China	59292
USA	39055
India	14317
United Kingdom	13769
Japan	11205
Other values (172)	149904

Length

Max length	38
Median length	5
Mean length	7.178370464
Min length	3

Characters and Unicode

Total characters	2064083
Distinct characters	54
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	18 ?
Unique (%)	< 0.1%

Sample

1st row	USA
2nd row	Australia
3rd row	Belgium
4th row	France
5th row	USA

Value	Count	Frequency (%)
China	59292	20.6%
USA	39055	13.6%
India	14317	5.0%
United Kingdom	13769	4.8%
Japan	11205	3.9%
Iran, Islamic Republic of	10465	3.6%
Canada	8615	3.0%
Taiwan	8488	3.0%
Germany	8407	2.9%
Italy	8340	2.9%
Other values (167)	105589	36.7%

Histogram of lengths of the category

Value	Count	Frequency (%)
china	59292	16.6%
usa	39055	10.9%
republic	19978	5.6%
of	18353	5.1%
united	14348	4.0%
india	14317	4.0%
kingdom	13769	3.9%
japan	11205	3.1%
iran	10465	2.9%
islamic	10465	2.9%
Other values (194)	145467	40.8%

Most occurring characters

Value	Count	Frequency (%)
a	289540	14.0%
i	202814	9.8%
n	197895	9.6%
e	107316	5.2%
r	81916	4.0%
l	78047	3.8%
C	71924	3.5%
d	70136	3.4%
	69172	3.4%
h	67799	3.3%
Other values (44)	827524	40.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1560299	75.6%
Uppercase Letter	416232	20.2%
Space Separator	69172	3.4%
Other Punctuation	18379	0.9%
Dash Punctuation	1	< 0.1%

Most frequent character per category

Value	Count	Frequency (%)
a	289540	18.6%
i	202814	13.0%
n	197895	12.7%
e	107316	6.9%
r	81916	5.3%
l	78047	5.0%
d	70136	4.5%
h	67799	4.3%
o	64066	4.1%
u	47597	3.1%
Other values (16)	353173	22.6%

Value	Count	Frequency (%)
C	71924	17.3%
S	59595	14.3%
U	54144	13.0%
A	51769	12.4%
I	46956	11.3%
R	24330	5.8%
K	22217	5.3%
T	17348	4.2%
J	11638	2.8%
G	11506	2.8%
Other values (14)	44805	10.8%

Value	Count	Frequency (%)
,	18353	99.9%
'	26	0.1%

Value	Count	Frequency (%)
	69172	100.0%

Value	Count	Frequency (%)
-	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1976531	95.8%
Common	87552	4.2%

Most frequent character per script

Value	Count	Frequency (%)
a	289540	14.6%
i	202814	10.3%
n	197895	10.0%
e	107316	5.4%
r	81916	4.1%
l	78047	3.9%
C	71924	3.6%
d	70136	3.5%
h	67799	3.4%
o	64066	3.2%
Other values (40)	745078	37.7%

Value	Count	Frequency (%)
	69172	79.0%
,	18353	21.0%
'	26	< 0.1%
-	1	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2064083	100.0%

Most frequent character per block

Value	Count	Frequency (%)
a	289540	14.0%
i	202814	9.8%
n	197895	9.6%
e	107316	5.2%
r	81916	4.0%
l	78047	3.8%
C	71924	3.5%
d	70136	3.4%
	69172	3.4%
h	67799	3.3%
Other values (44)	827524	40.1%

CountryCode
Categorical

HIGH CARDINALITY

Distinct	177
Distinct (%)	0.1%
Missing	2
Missing (%)	< 0.1%
Memory size	568.1 KiB

CHN	59292
USA	39055
IND	14317
GBR	13769
JPN	11205
Other values (172)	149904

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	862626
Distinct characters	26
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	18 ?
Unique (%)	< 0.1%

Sample

1st row	USA
2nd row	AUS
3rd row	BEL
4th row	FRA
5th row	USA

Value	Count	Frequency (%)
CHN	59292	20.6%
USA	39055	13.6%
IND	14317	5.0%
GBR	13769	4.8%
JPN	11205	3.9%
IRN	10465	3.6%
CAN	8615	3.0%
TWN	8488	3.0%
DEU	8407	2.9%
ITA	8340	2.9%
Other values (167)	105589	36.7%

Histogram of lengths of the category

Value	Count	Frequency (%)
chn	59292	20.6%
usa	39055	13.6%
ind	14317	5.0%
gbr	13769	4.8%
jpn	11205	3.9%
irn	10465	3.6%
can	8615	3.0%
twn	8488	3.0%
deu	8407	2.9%
ita	8340	2.9%
Other values (167)	105589	36.7%

Most occurring characters

Value	Count	Frequency (%)
N	123923	14.4%
A	84438	9.8%
C	76767	8.9%
S	70958	8.2%
U	70889	8.2%
R	67838	7.9%
H	65595	7.6%
I	38163	4.4%
P	30612	3.5%
T	30041	3.5%
Other values (16)	203402	23.6%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	862626	100.0%

Most frequent character per category

Value	Count	Frequency (%)
N	123923	14.4%
A	84438	9.8%
C	76767	8.9%
S	70958	8.2%
U	70889	8.2%
R	67838	7.9%
H	65595	7.6%
I	38163	4.4%
P	30612	3.5%
T	30041	3.5%
Other values (16)	203402	23.6%

Most occurring scripts

Value	Count	Frequency (%)
Latin	862626	100.0%

Most frequent character per script

Value	Count	Frequency (%)
N	123923	14.4%
A	84438	9.8%
C	76767	8.9%
S	70958	8.2%
U	70889	8.2%
R	67838	7.9%
H	65595	7.6%
I	38163	4.4%
P	30612	3.5%
T	30041	3.5%
Other values (16)	203402	23.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	862626	100.0%

Most frequent character per block

Value	Count	Frequency (%)
N	123923	14.4%
A	84438	9.8%
C	76767	8.9%
S	70958	8.2%
U	70889	8.2%
R	67838	7.9%
H	65595	7.6%
I	38163	4.4%
P	30612	3.5%
T	30041	3.5%
Other values (16)	203402	23.6%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	PY	SC	Technology	ComputerScience	NR	TCperYear	NumAuthors	Organisation	Region	Country	CountryCode
0	1998	Computer Science; Engineering	1.0	1	13	0.545455	3	Collaboration	North America	USA	USA
1	1998	Computer Science; Engineering	1.0	1	24	0.363636	2	Collaboration	SouthEast Asia and Pacific	Australia	AUS
2	1998	Computer Science; Engineering	1.0	1	13	3.454545	4	Collaboration	Western Europe	Belgium	BEL
3	1998	Computer Science; Engineering	1.0	1	13	3.454545	4	Collaboration	Western Europe	France	FRA
4	1998	Computer Science; Engineering	1.0	1	12	0.136364	2	Academia	North America	USA	USA
5	1998	Computer Science; Engineering	1.0	1	19	1.772727	2	Collaboration	South Asia	India	IND
6	1998	Computer Science; Engineering	1.0	1	34	1.181818	2	Academia	North America	USA	USA
7	1998	Computer Science; Engineering	1.0	1	23	0.181818	3	Academia	Western Europe	United Kingdom	GBR
8	1998	Computer Science; Engineering	1.0	1	14	3.136364	3	Collaboration	Western Europe	Germany	DEU
9	1998	Computer Science; Engineering	1.0	1	17	0.409091	3	Academia	North America	USA	USA

Last rows

	PY	SC	ArtsHumanities	LifeSciencesBiomedicine	SocialSciences	Health	NR	TCperYear	NumAuthors	Organisation	Region	Country	CountryCode
287534	2017	General & Internal Medicine	0.0	1.0	0.0	1	21	0.666667	2	Academia	Western Europe	United Kingdom	GBR
287535	2018	Business & Economics; Biomedical Social Sciences	0.0	0.0	1.0	0	3	0.000000	1	Academia	NorthEast Asia	China	CHN
287536	2016	Cultural Studies	0.0	0.0	1.0	0	32	0.000000	1	Academia	SouthEast Asia and Pacific	Australia	AUS
287537	2018	History	1.0	0.0	0.0	0	66	0.000000	1	Academia	Western Europe	Netherlands	NLD
287538	2015	Business & Economics	0.0	0.0	1.0	0	53	0.200000	1	Collaboration	Western Europe	United Kingdom	GBR
287539	2015	Business & Economics	0.0	0.0	1.0	0	33	0.200000	2	Collaboration	North America	Canada	CAN
287540	2009	Business & Economics	0.0	0.0	1.0	0	60	0.000000	2	Academia	North America	USA	USA
287541	2001	Literature	1.0	0.0	0.0	0	22	2.368421	2	Academia	North America	USA	USA
287542	2018	Literature	1.0	0.0	0.0	0	34	0.000000	1	Academia	Western Europe	Switzerland	CHE
287543	2017	Literature	1.0	0.0	0.0	0	45	0.000000	1	Academia	Western Europe	United Kingdom	GBR

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Cramér's V (φc)

Missing values

Sample

First rows

Last rows